import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from concurrent.futures import ProcessPoolExecutor
# 多进程编程
# 耗CPU操作，用多进程编程。对于IO操作，使用多线程，进程切换代价高于线程

# 1、对于耗费CPU的操作，多进程优于多线程
# def fib(n):
#     if n<2:
#         return 1
#     return fib(n-1)+fib(n-2)
#
#
# if __name__ == '__main__':
#     with ProcessPoolExecutor(3) as executor:
#         all_task = [executor.submit(fib, (num)) for num in range(25, 30)]
#         start_time = time.time()
#         for future in as_completed(all_task):
#             data = future.result()
#             print('ext result:{}'.format(data))
#
#         print('last time is {}'.format(time.time()-start_time))

# 2 对于IO操作，多线程优于多进程
def random_sleep(n):
    time.sleep(n)
    return n

if __name__ == '__main__':
    with ThreadPoolExecutor(3) as executor:
        all_task = [executor.submit(random_sleep, (num)) for num in [2]*30]
        start_time = time.time()
        for future in as_completed(all_task):
            data = future.result()
            print('ext result:{}'.format(data))

        print('last time is {}'.format(time.time()-start_time))

